Paste the standards (concentration and signal) and the sample readings. The calculator fits the line, checks linearity, computes the limits of detection and quantitation and gives each sample concentration with a confidence interval.
Pre-sizing and estimating tool: results do not replace design, calculations or reports signed by a licensed professional, nor verification against the applicable codes and standards.
Standards, fitted line and samples read off the curve.
Measured minus predicted signal, with a ±2 s_y/x band.
Concentration from the curve, 95% confidence interval and status against LOD, LOQ and the calibrated range.
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The calculation report gathers this page's inputs, results, equations, assumptions and references, with fields for project, engineer and revision. The full report also includes the charts and interpretations, in color. In the print dialog, choose Save as PDF.
It is the relation between the known concentration of standards and the signal the instrument reads (absorbance, peak area, mV). Once the line is fitted, it turns an unknown sample signal into concentration. In the example the line is y = 0.09963 x + 0.00167 and Sample A, with a mean signal of 0.3524, is 3.520 mg/L.
ISO 8466-1 recommends at least 5 levels, preferably 10, evenly spread over the range and including the blank. With fewer than 5, linearity tests lose power. Reading each standard in duplicate helps show repeatability.
No. A high R² can hide curvature, especially with standards bunched at the low end. Look at the residual plot: residuals should scatter randomly around zero. The ISO 8466-1 Mandel test compares the line with a parabola and tells whether curvature is significant.
From the curve deviation and slope: LOD = 3.3 · s ÷ b and LOQ = 10 · s ÷ b, as in ICH Q2. In the example, s_y/x = 0.00248 and b = 0.0996 give an LOD of 0.082 mg/L and an LOQ of 0.249 mg/L. For EPA compliance work, the method detection limit follows 40 CFR 136 Appendix B instead, which uses spiked samples.
Only if the intercept is not statistically different from zero and the blank has been subtracted. The calculator runs that t-test; in the example the 0.00167 intercept is not different from zero. Forcing the origin with a real intercept distorts low results, right near LOD and LOQ.
It is the range where the true concentration should lie with 95% confidence, given the noise of the curve and of the readings. It is narrowest at the center of the curve and widest at the ends. Reading the sample more times and using more standards narrow it.
Do not extrapolate: dilute the sample so it falls mid-range, read it again and enter the dilution factor, which the calculator multiplies into the result. Extrapolating assumes the response stays linear where it was never checked.
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